Signal processing method, signal processing circuit and information recording/regenerating apparatus

ABSTRACT

A partial response is utilized to record information on a medium and then regenerate the information from the medium. A regenerating system undergoes equalization including subjecting a regeneration signal from the medium to the convolution of
 
(k−s·D)
         (where D is one (1) bit delay operator, and   k and s are positive integer).
 
Such convolution is performed in the regenerating system so that low-frequency band noises are reduced with an improved error rate. The information is decoded from the equalized signal by use of maximum-likelihood detection.

This application is a continuation of U.S. patent application Ser. No.10/763,058, filed Jan. 22, 2004, which is a continuation ofInternational PCT Application No. PCT/JP01/06506 filed Jul. 27, 2001.

TECHNICAL FIELD

The present invention relates generally to a signal processing method,signal processing circuit and information recording/regeneratingapparatus utilizing a partial response, and more particularly, to asignal processing method, signal processing circuit and informationrecording/regenerating apparatus best suited to perform high densityrecording with reduced medium noises.

BACKGROUND ART

Recently, recording density of magnet disk units is dramaticallyincreasing. This is largely attributable to a highly-sensitive MR head(Magneto-Resistive effect head). Simultaneously, this is also largelyattributable to practical use of PR4ML (Partial Response class 4Maximum-Likelihood) method which can perform regeneration with low S/Nratio as signal processing method, rather than conventional peakdetection method. The PR4ML method removes waveform intervention byutilizing partial response, reduces noises by lowering a frequency band,and performs convolution according toU(T)=(1−D)·(1+D)^(n)

D: delay operator indicating one (1) bit delay, and then, finds a signalwith maximum-likelihood from regeneration signals containingdisturbances such as noises by a maximum-likelihood detecting circuitwith Viterbi algorithm. At this point, the convolution of (1+D) has thetransfer constant shown in FIG. 1, and is improved to increase the ordern to 2 or 3, in order to reduce noises of high-frequency band. As aresult, though the maximum-likelihood detecting circuit becomes morecomplicated, error rate is improved. The order n is limited up to 3, andin case that it was increased to more than 3, improvement of the errorrate was little. In the noises regenerated in magnetic recording, thelarge power noises are contained in a low-frequency band, rather than ahigh-frequency band. Most of the noises in the high-frequency band aredistributed substantially uniformly throughout the bandwidth of noisessuch as pre-amplifier noises and MR head noises. Contrary, a peak ofpower of medium noises is present relatively near the low-frequencyband, partially depending on materials of recording medium. Recently,since an area of one (1) bit is closing in on that of particles ofmagnetic materials, the medium noises are increasing, therefore somerecording medium have the marked peak of power in low-frequency band, asshowing in FIG. 2. Also, side-crosstalk from adjacent tracks becomeslarger in lower frequency band, because of the nature thereof.Conventionally, it is believed that the convolution of (1+D) is enoughfor the noises in low-frequency band. In this point, it is believed thatthe convolution of (1+D) has transfer characteristic showing in FIG. 3,and reduces the noises in low-frequency band. However, since thisconvolution in magnetic recording is actually performed in a recordingsystem before generation of the medium noises, and an equalizing targetthereof is characteristic showing in FIG. 4, therefore the convolutionof (1+D) does not act on the noises in low-frequency band at all, andmedium noises is not affected by the transfer characteristic with theconvolution of (1+D).

DISCLOSURE OF THE INVENTION

According to the present invention, there are provided a signalprocessing method, signal processing circuit and informationrecording/regenerating apparatus utilizing partial response to reducethe noises in low-frequency band and improve recording density.

According to the present invention, there are also provided a signalprocessing method, signal processing circuit and informationrecording/regenerating apparatus utilizing partial response to reducethe medium noises and improve the regeneration error rate.

According to the present invention, there are provided a signalprocessing method, signal processing circuit and informationrecording/regenerating apparatus utilizing partial response to reduceside-crosstalk and improve the regeneration error rate.

The present invention provides a signal processing method utilizing apartial response to record information on a medium and then regeneratethe information from the medium, wherein a regeneration signal from themedium is subjected to an equalizing process including the convolutionof(k−s·D)

where D: one (1) bit delay operator, and

k, s: positive integer, k≠s.

In the present invention, the information is decoded from the signalequalized through the convolution of (k−s·D), by use ofmaximum-likelihood detection. In this manner, by performing aconvolution of (k−s·D) in a regenerating system, the present inventioncan reduce low-frequency band noises and improve the error rate. Also,by making the convolution as (k−s·D) and optimizing k and s, it ispossible to obtain optimum filter characteristics suitable forcharacteristics of the medium noises and improve the error rate.

The present invention provides a signal processing circuit utilizing apartial response to record information on a medium through a recordingsystem and regenerate the information from the medium through aregenerating system, wherein the regenerating system includes anequalizer subjecting a regeneration signal from the medium to theconvolution of(k−s·D)

where D: one (1) bit delay operator, and

k, s: positive integer, k≠s.

The signal processing circuit comprises a maximum-likelihood detectorwhich decodes the information from an output signal of the equalizer byuse of maximum-likelihood detection.

The present invention provides a signal recording/regenerating apparatusutilizing a partial response to record information on a medium through arecording system and regenerate the information from the medium througha regenerating system, wherein the regenerating system includes anequalizer subjecting a regeneration signal from the medium to theconvolution of(k−s·D)

where D: one (1) bit delay operator, and

k, s: positive integer, k≠s.

The signal recording/regenerating apparatus comprises amaximum-likelihood detector which decodes the information from an outputsignal of the equalizer by use of maximum-likelihood detection.

The present invention provides a signal processing method utilizing apartial response to record information on a medium and then regeneratethe information from the medium, wherein a record signal recorded on themedium is subjected to the convolution of(1−D)

where D: one (1) bit delay operator, and wherein a regeneration signalfrom the medium is subjected to an equalizing process including theconvolution of(k−s·D)·(1+D)^(n)

where D: one (1) bit delay operator,

k, s: positive integer, and

n: positive integer, except 2.

The information is decoded from the thus equalized signal by use ofmaximum-likelihood detection.

By performing the convolution of (k−s·D) in the regenerating system, inaddition to the convolution of (1−D) for input signals in the recordingsystem (which has no effect to reduce low-frequency noises), the presentinvention can reduce noises in the low-frequency band. By performing theconvolution of (1−D) in the regenerating system, the present inventioncan reduce noises in the high-frequency band. Also, by making theconvolution as (k−s·D) and optimizing k and s, it is possible to obtainoptimum filter characteristics suitable for characteristics of themedium noises and improve the error rate.

The present invention provides a signal processing circuit utilizing apartial response to record information on a medium through a recordingsystem and regenerate the information from the medium through aregenerating system, wherein the recording system includes a circuitunit subjecting a record signal recorded on the medium to theconvolution of(1−D)

where D: one (1) bit delay operator, and wherein the regenerating systemincludes an equalizer subjecting an output signal from the medium to theconvolution of(k−s·D)·(1+D)^(n)

where D: one (1) bit delay operator,

k, s: positive integer, and

n: positive integer, except 2.

A maximum-likelihood detector is further disposed which decodes theinformation from an output signal of the equalizer by use ofmaximum-likelihood detection.

The present invention provides a signal recording/regenerating apparatusutilizing a partial response to record information on a medium through arecording system and regenerate the information from the medium througha regenerating system, wherein the recording system includes a circuitunit subjecting a record signal recorded on the medium to convolution of(1−D)where D: one (1) bit delay operator, and wherein the regenerating systemincludes an equalizer subjecting a regeneration signal from the mediumto the convolution of(k−s·D)·(1+D)^(n),

where D: one (1) bit delay operator,

k, s: positive integer, and

n: positive integer, except 2.

A maximum-likelihood detector is further disposed which decodes theinformation from an output signal of the equalizer by use ofmaximum-likelihood detection.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a transfer characteristic diagram by the convolution of (1+D)effected in the conventional regenerating system;

FIG. 2 is a power spectrum characteristic diagram of medium noises;

FIG. 3 is a transfer characteristic diagram by the conventionalconvolution of (1−D) in the recording system;

FIG. 4 is a characteristic diagram of an equalizing target in aconventional PR4ML method;

FIG. 5 is a block diagram of a hard disk drive to which the presentinvention is applied;

FIG. 6 is a block diagram of a first embodiment of the present inventioncovering a (1−D)²·(1+D)¹ PRML structure;

FIG. 7 is a characteristic diagram of an equalizing target of the firstembodiment of FIG. 6;

FIG. 8 is a schematic chart of an impulse response waveform representedby an equalizer output of FIG. 6;

FIG. 9 is a block diagram of a read channel of FIG. 5, according to thefirst embodiment;

FIG. 10 is a transfer characteristic diagram of a head/medium system inFIG. 9;

FIG. 11 is a transfer characteristic diagram of an equalizer, includinga low-pass filter, of FIG. 9;

FIG. 12 is a schematic diagram representing relationship ofH(f)·Q(f)=R(f)·G(f), which gives equalizing target characteristic ofFIG. 7, by transfer characteristic diagrams;

FIG. 13 is a trellis diagram used by a maximum-likelihood detectingcircuit of FIG. 9;

FIG. 14 is a block diagram of the maximum-likelihood detecting circuitof FIG. 9;

FIG. 15A to FIG. 15I are time charts of record regeneration by(1−D)²·(1+D)¹ PRML;

FIG. 16 is a block diagram of a second embodiment of the presentinvention covering a (1−D)·(1−2D)·(1+D)¹ PRML structure;

FIG. 17 is a characteristic diagram of an equalizing target of thesecond embodiment of FIG. 16;

FIG. 18 is a schematic chart of an impulse response waveform representedby an equalizer output of FIG. 16;

FIG. 19 is a transfer characteristic diagram of an equalizer of FIG. 16;

FIG. 20 is a schematic diagram representing relationship ofH(f)·Q(f)=R(f)·G(f), which gives equalizing target characteristic ofFIG. 17, by transfer characteristic diagrams;

FIG. 21 is a trellis diagram used by a maximum-likelihood detectingcircuit of FIG. 16;

FIG. 22A to FIG. 22I are time charts of record regeneration by(1−D)·(1−2D)·(1+D)¹ PRML;

FIG. 23 is a block diagram of a third embodiment of the presentinvention covering a (1−D)·(3−2D)·(1+D)¹ PRML structure;

FIG. 24 is a characteristic diagram of an equalizing target of the thirdembodiment of FIG. 23;

FIG. 25 is a schematic chart of an impulse response waveform representedby an equalizer output of FIG. 23;

FIG. 26 is a transfer characteristic diagram of an equalizer of FIG. 23;

FIG. 27 is a schematic diagram representing relationship ofH(f)·Q(f)=R(f)·G(f), which gives equalizing target characteristic ofFIG. 24, by transfer characteristic diagrams;

FIG. 28 is a trellis diagram used by a maximum-likelihood detectingcircuit of FIG. 23;

FIG. 29A to FIG. 29I are time charts of record regeneration by(1−D)·(3−2D)·(1+D)¹ PRML;

FIG. 30 is a block diagram of a fourth embodiment of the presentinvention covering a (1−D)·(3−2D)·(1+D)² PRML structure;

FIG. 31 is a characteristic diagram of an equalizing target of thefourth embodiment of FIG. 30;

FIG. 32 is a schematic chart of an impulse response waveform representedby an equalizer output of FIG. 30;

FIG. 33 is a transfer characteristic diagram of an equalizer of FIG. 30;

FIG. 34 is a schematic diagram representing relationship ofH(f)·Q(f)=R(f)·G(f), which gives equalizing target characteristic ofFIG. 31, by transfer characteristic diagrams;

FIG. 35 is a trellis diagram used by a maximum-likelihood detectingcircuit of FIG. 30; and

FIG. 36A to FIG. 36I are time charts of record regeneration by(1−D)·(3−2D)·(1+D)² PRML.

BEST MODE FOR CARRYING OUT THE INVENTION

FIG. 5 is a block diagram of a hard disk drive to which the presentinvention is applied. In FIG. 5, the hard disk drive consists of a SCSIcontroller 10, a drive control 12 and a disk enclosure 14. Of course, aninterface with a host is not limited to the SCSI controller 10, and anysuitable interface controllers may be used. The SCSI controller 10 isprovided with MCU (Main Control Unit) 16, a memory 18 using DRAM or SRAMused as a control storage, a program memory 20 using a non-volatilememory such as a flash memory storing a control program, a hard diskcontroller (HDC) 22 and a data buffer 24. The drive controller 12 isprovided with drive logic 26, DSP 28, a read channel (RDC) 30 and aservo driver 32. Also, the disk enclosure 14 is provided with a head IC34, and compound heads 36-1 to 36-6 having recording heads andregenerating heads are connected to the head IC 34. The compound heads36-1 to 36-6 are provided to each recording surface of magnet disk units38-1 to 38-3, and moved to any track positions of the magnet disk units38-1 to 38-3, by driving a rotary actuator with VCM 40. The magnet diskunits 38-1 to 38-3 is rotated by a spindle motor 42 at a constant speed.

FIG. 6 is a block diagram of a basic structure in a first embodiment ofthe present invention, and in this first embodiment, (1−D)²·(1+D)¹ PRMLstructure is covered. A magnetic recording/regenerating system in thefirst embodiment is provided with an NRZI recording system 44, adifferential detector 46, a magnetic regenerating system 48, anequalizer 50 and a maximum-likelihood detecting circuit 52. In signalprocessing in the first embodiment, by step-by-step recording of inputcodes on the medium in the NRZI recording system 44 at the start,pre-coding of 1/(1−D) and a convolution operation of (1−D) can beperformed simultaneously. By performing differential detection of theinput codes recorded on the medium with the head as the differentialdetector 46, impulse generation is performed. At the MR(magnetoresistive effect head), by detecting vertical elements ofmagnetic flux, the same impulse generation as the differential detector46 is obtained. As head output, an impulse response waveform of transfercharacteristic H(f) of the magnetic regenerating system 48, whichdetermined by frequency characteristic of the medium and the head, isregenerated. The product of the transfer characteristic H(f) of themagnetic regenerating system 48 and transfer characteristic Q(f) of theequalizer 50 is characteristic which is equalizing target of theregenerating system, given by the product of transfer characteristicR(f) of a Nyquist equalizer and (1−D)·(1+D)=G(f).

Therefore the relationship is represented by following equation.H(f)·Q(f)=R(f)·G(f)  (1)

FIG. 7 shows the equalizing target characteristic of the regeneratingsystem in the first embodiment of FIG. 6, given by the equation (1). Inthis figure, characteristic 56 shown by a dotted line is cosine roll-offcharacteristic R(f) of the Nyquist equalizer, and fn is a Nyquistfrequency. Comparing equalizing target characteristic 54 of firstembodiment of FIG. 7 with conventional equalizing target characteristicof FIG. 4, in equalizing target characteristic 54 of first embodiment,gain is substantially reduced in low-frequency band.

The transfer characteristic Q(f) of the equalizer 50 of FIG. 6 toachieve these equalizing target characteristic 54 is adjusted toQ(f)=R(f)/{H(f)·G(f)}  (2)according to the equation (1). In output of the equalizer 50 adjusted tothe transfer characteristic Q(f) of the equation (2), an impulseresponse waveform 58 showing in FIG. 8 is obtained. In this impulseresponse waveform 58, a partial response equalizing waveform, whichbecomes +1 at time −1, −1 at time +1T and 0 at other time ±nT (n isinteger), is obtained. At this point, time T is T=1/fn. Further, animpulse response waveform 60 shown by the dotted line is a waveformcorresponding to a negative impulse. This impulse response waveform is,for convenience of description, shown by a waveform without noises, butactually is in the form with convoluted noises, and fluctuates with thenoises around the value.

The maximum-likelihood detecting circuit 52 of FIG. 6 detects theconvolution code from the partial response equalizing waveform with theconvoluted noises output from the equalizer 50, according to Viterbialgorithm. In the first embodiment, since convolution of (1−D) in theNRZI recording system 44 and convolution of (1−D)·(1+D) in the magneticregenerating system 48 are performed, by expanding these expression, afollowing one is obtained.(1−D)²·(1+D)=1−D−D ² +D ³

Therefore, it detects the convolution code “1, −1, −1, 1” correspondingto the input code “1”, and output an output code.

At this point, in the magnetic regenerating system 48, the convolutionof (1−D) to limit the gain in the low-frequency band is represented by(k−s·D) as the general type. Thus, the first embodiment is in the caseof k=1 and s=1. Further, the overall convolution, including therecording system and the regenerating system, is generally representedby following one.(1−D)·(k−s·D)·(1+D)^(n)Therefore, it is understood that, in the first embodiment, theconvolution of (1+D)^(n) to attenuate the gain in the high-frequencyband is in the case of n=1.

FIG. 9 is a block diagram when applying the first embodiment of thepresent invention of FIG. 6 to a read channel 30 used in a hard diskdrive of FIG. 5. In FIG. 9, the recording system consists of an encoder62, a write compensation circuit 64, an NRZI converting circuit 66, awrite amplifier 68 and a write head 70. The regenerating system consistsof a read head 72, a pre-amplifier 74, AGC circuit 76, a low-pass filter78, a sample circuit 80, an equalizer 82, a maximum-likelihood detectingcircuit 84, a decoder 86 and a VFO circuit 88. For the read channel ofFIG. 9, the operation thereof is described as bellow. Input data isconverted to the code that the number of successive zero (0) is limited,such as the 8/9 RLL code, on the encoder 62. The write compensationcircuit 64 moves the recording location slightly in advance tocompensate NLTS (Non-Linear Transition Shift). The NRZI convertingcircuit 66 is composed of single-step flip-flop, and converts RZ (Returnto Zero) code to NRZI (Non-Return to Zero Interleave) code. In thisconversion on the NRZI converting circuit 66, pre-coding of 1/(1−D) andconvolution operation of (1−D) are performed effectively. The writeamplifier 68 sends a recording current corresponding to the data to thewrite head 70, activates it, and makes it magnetically record the dataon the medium which is not shown. The read head 72 has differentialdetecting characteristic to detect change in magnetization of themedium, therefore the data recorded step-by-step is detected by the readhead 72 as differentiated impulses. At the same time, since the mediumhas the transfer characteristic corresponding to the frequencycharacteristic thereof, the impulse response waveform known as theapproximate expression of Lorentz is output from the read head 72. Thischaracteristic H(f) determined by the frequency characteristics of themedium and the head would be, for example, as shown in the transfercharacteristic 90 of FIG. 10, the characteristic being larger in thelower-frequency band, and more attenuated in the higher-frequency.Referring to FIG. 9 again, after amplified by pre-amplifier 74, the headregeneration signal is additionally controlled at constant amplitude atthe AGC circuit 76, and its unnecessary noises are removed by thelow-pass filter 78. The low-pass filter 78 constitutes a part of theequalizer 82 in the subsequent stage. The sample circuit 80 samples andholds the regeneration signal with the clock from the VFO circuit 88, ordigitizes with an A/D converter. The equalizer 82 consists of atransversal filter and the like, the transfer characteristic thereof iscoordinated so that the product with the transfer characteristic of thelow-pass filter 78 in the preceding stage becomes the transfercharacteristic Q(f) which is represented by the equation (2). Theequalizer 82 may be the adaptable type which performs automaticcoordination corresponding to the regeneration signal. FIG. 11 shows thetransfer characteristic of the equalizer 82 including the low-passfilter 78, as schematic characteristic 92. The equalizer transfercharacteristic Q(f) given by the characteristic 92 in the firstembodiment would be characteristic substantially attenuated in thelow-frequency band and boosted in high-frequency band, then attenuatedwith Nyquist frequency fn. Referring to FIG. 9 again, the VFO circuit 88is one which generates a clock signal synchronized to the regenerationsignal, and may be achieved with the method disclosed in, for example,publication No. JP1-143447. Also, by splitting the equalizer circuit 82into parts of a (1+D) filter and a (1−D) filter, and inputting theoutput of the (1+D) filter into the VFO circuit 88, it is achieved byprior art.

FIG. 12 shows the relationship of the equation (1) which givesequalizing target characteristic 54 of FIG. 7, by transfercharacteristic diagrams.

In FIG. 12, the right side of the equation (1) is given by the productof the cosine roll-off characteristic R(f) of the Nyquist equalizer andG(f) which is convolution of (1−D)·(1+D), as shown by the upper part ofFIG. 12. Also, the left side of the equation (1) is the product of thetransfer characteristic H(f) of the magnetic regenerating system and theequalizer transfer characteristic Q(f), as shown by the lower part ofthe figure, and this gives the equalizing target characteristic 54 inthe middle part. Therefore, from the equation (2) which is obtained bydividing the equalizing target characteristic 54, given by theR(f)×G(f), by the transfer characteristic H(f) of the magneticregenerating system, the transfer characteristic Q(f) of the equalizer82 to be adjusted may be obtained.

Now, the maximum-likelihood detecting circuit 84 of FIG. 9 is described.The maximum-likelihood detecting circuit 84 operates so that theconvolution code “1, −1, −1, 1” is detected with Viterbi algorithm, intime sequence, from the partial response equalizing waveform output fromthe equalizer 82.

FIG. 13 is a trellis diagram showing possible combinations of theconvolution code “1, −1, −1, 1”. In this trellis diagram, eight (8)nodes related to three (3) bits from (n−3) bit to (n−1) bit of the leftpart are illustrated. In the right part, three (3) bits from (n−2) bitto n bit, which are advanced one (1) bit, are illustrated, and the nextbit is “0” or “1”, so if the next bit is “0”, transition to thecondition of dotted line will be occur, and if the next bit is “1”,transition to the condition of solid line will be occur. Further,possible voltage values at this point are shown above and bellow thethree (3) bits in the left part. The voltage values take values “+2, +1,0, −1, −2” which is combined by addition when the convolution code “1,−1, −1, 1” is mismatched within the overlapping range. Since, whenconvoluting one (1) bit into four (4) bits, the constraint length=4,leading three (3) bits are affected by preceding bits, but the forth bitis not affected, and determined uniquely. For example, when the leadingthree (3) bits from (n−3) bit to (n−1) bit are “000”, if the voltagevalue is 0, nth bit will move to “0” as the top dotted line, and if thevoltage value is +1, nth bit will move to “1” as the next solid line.Now, the maximum-likelihood detecting method using the trellis diagramof FIG. 13 is described. In the principle of the maximum-likelihooddetection, by squaring the difference between the voltage valuesconsidered to be the trellis diagram target and the actual samplevoltage (not matched to the target voltage value, because of thenoises), and cumulatively adding the results for each bit, thecumulative square error is obtained. After obtaining the cumulativesquare errors for all the possible combination shown in the trellisdiagram, the combination (path) which has the smallest cumulative squareerror is detected as one with maximum-likelihood.

FIG. 14 is a block diagram showing a concrete example of themaximum-likelihood detecting circuit 84 of FIG. 9. In a cumulativesquare error detecting circuit 94, the square error is detected fromdifference between 16 voltage values which is considered to be targetsof the trellis diagram in FIG. 13 and the sample values of the partialresponse equalizing waveform. A cumulative square error retainingcircuit 100 retains eight (8) node cumulative square errorscorresponding to eight (8) nodes in the trellis diagram of FIG. 13. Acumulative square error calculating circuit 96 calculates new 16 branchcumulative square errors by adding eight (8) node cumulative squareerrors and 16 node cumulative square errors, respectively. A compare andselect circuit 98 compares the branch cumulative square errors indicatedby two arrows related to each node in the right part of the trellisdiagram of FIG. 13, determines that smaller data has higher likelihood,and outputs the data and select signals to a path memory 102.

Simultaneously, it outputs the branch cumulative square errorcorresponding to the selected data to the cumulative square errorretaining circuit 100 as new node cumulative square error for that node.The path memory 102 consists of multi-stage registers recording theselected path, records the selected data from the compare and selectcircuit 98, and copies the data in each stage according to the selectsignal, as shown in the trellis diagram of FIG. 13. In this way, onehalf of paths continues to exist in each stage, and the other halfdisappears. By repeating these comparison and selection of the paths,the path with maximum-likelihood will continues to exist till the last,and the maximum-likelihood detection will be done. The detected codeconsidered as one with maximum-likelihood in path memory 102 isprocessed in a post-coder 104 into the detected data, and finally, by9/8 conversion in the decoder 86 of FIG. 9, into the data.

FIG. 15A to FIG. 15I are time charts which give detail description ofprocess in the recording/regenerating systems of FIG. 9 and FIG. 14. Thedata of FIG. 15A is converted to 8/9 RLL code in which every eight (8)bits is converted to nine (9) bits, and becomes the input data of FIG.15B. In the process of NRZI converting circuit 66, 1/(1−D) is calculatedfirstly, and this is equivalent to applying the logic operationexclusive-OR to the input code and the last data before the result of1/(1−D) operation. The convolution of (1−D) is equivalent to subtractingthe 1/(1−D) operation result which is delayed once. These 1/(1−D) and(1−D) operations are equivalently performed in the single-stageflip-flop of the NRZI converting circuit 66. Further, the writeamplifier drives the write head 70, so that the direction of recordingcurrent is reversed whether the value is “1” or “−1”. The signalrecorded on the medium is converted to impulse by differential detectingaction of the read head of FIG. 15D, and the impulse response waveformlike FIG. 15E is obtained as head output, depending on the transfercharacteristics of the medium and the head. The equalizer 82 consistsof, for example, 10 tap transversal FIR filters, and, as shown in FIG.15F, by repeating the adjustment of each tap gain of the equalizer 82corresponding to the offset amount of the sample point voltage from thefive (5) values of ±2, ±1 and 0, automatic adjustment to the targettransfer characteristic Q(f) such as FIG. 11 may be performed. Anequalizer provided with the automatic adjustment function is calledadaptable type equalizer, and the adaptation method thereof is calledthe steepest descent method. As a result, the sample point voltageoutput from the equalizer 82 is “+2, +1, 0, −1” as shown by black dotsof FIG. 15F, and considered to be the partial response waveform which issubjected to Nyquist equalizing. By the way, the waveform without noisesis shown in FIG. 15, for convenience of description, but actually, thewaveform has convoluted noises. If the noises are convoluted, theoperation of the equalizer 82 doesn't change basically. In themaximum-likelihood detecting circuit 84, the convolution code isdetected according to the description of FIG. 14. In FIG. 15G, the solidline shows the path continued to exist through this maximum-likelihooddetection, and the dotted lines show the disappeared paths. The datadetected by this maximum-likelihood detection method is processed in thepost-coder 104 into the output code of FIG. 15H, then, subjected to the9/8 conversion in the decoder 86 of FIG. 9, and becomes the data of FIG.15I.

FIG. 16 is a block diagram of a second embodiment of the presentinvention, and the second embodiment is wherein (1−D)·(1−2D)·(1+D) PRMLstructure is covered. In FIG. 16, the second embodiment consists of theNRZI recording system 44, the differential detector 46, the magneticregenerating system 48, an equalizer 106 and a maximum-likelihooddetecting circuit 108. Among these, from the NRZI recording system 44 tothe magnetic regenerating system 48 are basically same as the firstembodiment in FIG. 6. The transfer characteristic Q(f) of the equalizer106 is expressed by equation (2), except G(f) in the right side of theequation (2). More specifically, in the second embodiment, the equationis as follows.G(f)=(2−D)·(1+D)¹  (3)In this case, the equalizing target characteristic given by R(f)·G(f) isthe characteristic 110 of FIG. 17. It is noted that the characteristic56 is cosine roll-off characteristic R(f) of the Nyquist equalizer. Itis understood that the convolution of (2−D)·(1+D) which is theconvolution in the magnetic regenerating system 48 and the equalizer 106of the first embodiment is in the case of k=2, s=1, and n=1 for thegeneral type (k−s·D)·(1+D)^(n). From the equalizing targetcharacteristic given by the characteristic 110 of FIG. 17, the impulseresponse waveform 112 shown by FIG. 18 is obtained from output of theequalizer 106. In this impulse response waveform 112, the partialresponse equalizing waveform, which is +2 at time 0, −1 at time 1T, −1at time 2T, and 0 at other times ±nT (n is integer), is obtained. Inthis figure, the dotted line is the partial response equalizing waveform114 corresponding to a negative impulse. Further, FIG. 18 shows, forconvenience of description, the waveform without noises, but actually itis the waveform with convoluted noises, and fluctuates around the value.The maximum-likelihood detecting circuit 108 of FIG. 16 receives thepartial response equalizing waveform with convoluted noise output fromthe equalizer 106, and detects the convolution code according to Viterbialgorithm. In the second embodiment, the convolution of (1−D) in therecording system and the convolution of (2−D)·(1+D)¹ in the regeneratingsystem has been done, therefore, expansion to(1−D)·(2−D)·(1+D)=2−D−2D ² +D ³is possible. Therefore, to the input code “1”, convolution code “2, −1,−2, 1” is detected, and the output code is output.

Now, specific structure in the case that the second embodiment of FIG.16 is applied to the read channel 30 which is provided to the hard diskdrive of FIG. 2 is described. A block diagram in the case that thesecond embodiment is applied to the read channel 30 is same as the firstembodiment of FIG. 9, also the functions thereof from the recordingsystem to the sample circuit 80 of the regenerating system are basicallysame as the first embodiment of FIG. 9, and the equalizer 82 and themaximum-likelihood detecting circuit 84 have structure and operationunique to the second embodiment. The transfer characteristic Q(f) of theequalizer circuit 84 in the second embodiment, including the transfercharacteristic of the low-pass filter 78, is shown by transfercharacteristic 116, schematically. In this figure, characteristic 92shown by a dotted line is the equalizer transfer characteristic of thefirst embodiment. When comparing the equalizer transfer characteristic92 of the first embodiment to the equalizer transfer characteristic 116of the second embodiment, it is understood that, by performing theconvolution of (2−D) of the second embodiment corresponding to theconvolution of (1−D) of the first embodiment, the gain in thelow-frequency band is increased.

FIG. 20 shows the relationship of the equation (1) which givesequalizing target characteristic 110 of FIG. 17 in the secondembodiment, by transfer characteristic diagrams. In FIG. 20, the upperpart shows R(f)×G(f) in the right side of the equation (1) wherein G(f)is the convolution in the regenerating system, since, in the secondembodiment, the convolution attenuating the low-frequency band is (2−D),the gain in the low-frequency is larger than (1−D) shown by the dottedline of the first embodiment. By multiplication of the G(f) and thecosine roll-off characteristic R(f) of the Nyquist equalizer, equalizingtarget characteristic 110 of the second embodiment in the middle part ofFIG. 19 is obtained. This equalizing target characteristic 110 isequivalent to the product of the transfer characteristic H(f) of themagnetic regenerating system in the left side of the equation (2) andthe equalizing transfer characteristic Q(f). Therefore, the equalizingtransfer characteristic Q(f) may be adjusted to the characteristic ofthe equation (2) wherein the equalizing target characteristic 110 givenby R(f)·G(f) is divided by the magnetic regenerating transfercharacteristic H(f). In this point, the VFO circuit 88 of FIG. 9 used inthe second embodiment may be achieved by prior art, by splitting theequalizer 82 into parts of a (1+D) filter and a (1−D) filter, andinputting the output of the (1+D) filter into the VFO circuit 88.

The maximum-likelihood detecting circuit of the second embodiment, whichis basically same as that of the first embodiment shown in FIG. 14,operates so that the convolution code “2, −1, −2, 1” is detected withViterbi algorithm, in time sequence. FIG. 21 shows a trellis diagramshowing possible combinations of the convolution code of the secondembodiment. In this case, again, since one (1) bit is convoluted intofour (4) bits, the constraint length=4. The detected code considered asone with maximum-likelihood in this way is processed in a post-coder 104in FIG. 14 into the detected data, and finally, by 9/8 conversion in thedecoder 86, into the decoded data, in the same way as the firstembodiment of the FIG. 9.

FIG. 22A to FIG. 22I are time charts which show details of recording andregenerating in the second embodiment. Since the data of FIG. 22A to thehead output of FIG. 22E are basically same as FIG. 15A to FIG. 15E,those are not described bellow. The equalizer of FIG. 22E consists of,for example, 10 tap transversal FIR filters, and the sample pointvoltage takes seven (7) values “+3, +2, +1, 0, −1, −2, −3” because ofthe convolution code of “2, −1, −2, 1” overlapping each other,therefore, the partial response equalizing waveform which is Nyquistequalized is output as shown. The maximum-likelihood detecting circuitof FIG. 22G performs maximum-likelihood detection with Viterbi algorithmaccording to the trellis diagram in FIG. 21, and output the output codeof FIG. 22H. Finally, 9/8 conversion is performed in the decoder, andthe data of FIG. 22I is output.

FIG. 23 is a third embodiment of the present invention, and the thirdembodiment is wherein (1−D)·(3−2D)·(1+D)¹ PRML structure is covered. Inthe third embodiment, from the NRZI recording system 44 to the magneticregenerating system 48 are basically same as those of the firstembodiment in FIG. 6. The transfer characteristic Q(f) of the equalizer118 is expressed by equation (2), except the convolution G(f) in theregenerating system in the right side of the equation (2). In the thirdembodiment, G(f) isG(f)=(3−2D)·(1+D)¹.Therefore, the equalizing target characteristic of the third embodimentwhich is given by the product of G(f) of the equation (4) and the cosineroll-off characteristic R(f) of the Nyquist equalizer is thecharacteristic 122 of FIG. 24. In this figure, the characteristic 56shown by the dotted line is the cosine roll-off characteristic R(f) ofthe Nyquist equalizer. In this figure, the convolution in theregenerating system of the third embodiment is in the case of k=3, s=2,and n=1 for the general type (k−s·D)·(1+D)^(n).

The impulse response waveform 124 shown by FIG. 25 is obtained fromoutput of the equalizer 118, which has the equalizing targetcharacteristic as in FIG. 24. In this impulse response waveform 124, thepartial response equalizing waveform, which is +3 at time 0, +1 at time+1T, −2 at time 2T, and 0 at other times ±nT (n is integer), isobtained. In this figure, the dotted line is the partial responseequalizing waveform 126 corresponding to a negative impulse. Further,for convenience of description, the waveform without noises is shown,but actually it is the waveform with convoluted noises, and fluctuatesaround the value. The maximum-likelihood detecting circuit 120 of thethird embodiment detects the convolution code according to Viterbialgorithm from the partial response equalizing waveform with convolutednoises. In the third embodiment, the convolution of (1−D) in therecording system and the convolution of (3−2D)·(1+D)¹ in theregenerating system has been done, therefore, expansion to(1−D)·(3−2D)·(1+D)=3−2D−3D ²+2D ³is possible. Therefore, convolution code “3, −2, −3, 2” corresponding toinput code “1” is detected, and the output code is output.

A block diagram in the case that the third embodiment, which has thebasic structure of FIG. 23, is applied to the read channel 30 in thehard disk drive of FIG. 2 is same as the first embodiment of FIG. 9.More specifically, from the recording system to the sample circuit 80 ofthe regenerating system in FIG. 9 are basically same as the firstembodiment. The transfer characteristic Q(f) of the next equalizercircuit 82 of the third embodiment, including the transfercharacteristic of the low pass filter 78, is shown by characteristic 128of FIG. 26, schematically. In this figure, characteristic 92 shown by adotted line is the characteristic of the first embodiment of FIG. 11,and characteristic 116 shown by a dotted line is the characteristic ofthe second embodiment of FIG. 19. Therefore, characteristic 128 whichgives the equalizer transfer characteristic Q(f) in the third embodimentis in the middle of the characteristic 92 in the first embodiment andthe characteristic 116 in the second embodiment. In this point, the VFOcircuit 88 used in the third embodiment of FIG. 9 may be achieved byprior art, by splitting the equalizer 82 into parts of a (1+D) filterand a (1−D) filter, and inputting the output of the (1+D) filter intothe VFO circuit 88.

FIG. 27 shows the relationship of the equation (1) which givesequalizing target characteristic 122 of FIG. 24 in the third embodiment,by each transfer characteristic diagram. In FIG. 27, G(f) correspondingto the convolution in the regenerating system is given by the product of(3−2D) and (1+D), and (3−2D) takes the values middle of (1−D) of thefirst embodiment and (2−D) of the second embodiment, which are shown bythe dotted lines. Then, by calculating the product of G(f) and thecosine roll-off characteristic R(f) of the Nyquist equalizer, theequalizing target characteristic 122 of the third embodiment isobtained. Since the equalizing target characteristic 122 is equivalentto the product of the transfer characteristic H(f) and the equalizertransfer characteristic Q(f) in the recording system, by the equation(2) wherein divides the equalizing target characteristic 122 with thetransfer characteristic H(f) in the recording system, the equalizertransfer characteristic Q(f) may be obtained.

The maximum-likelihood detecting circuit 84 of the third embodiment inFIG. 9, which has basically same structure as that of the firstembodiment in FIG. 14, operates so that the convolution code “3, −2, −3,2” is detected with Viterbi algorithm, in time sequence. FIG. 28 shows atrellis diagram showing possible combinations of the convolution code ofthe third embodiment. In this case, since one (1) bit is convoluted intofour (4) bits, the constraint length=4. The detected code considered asone with maximum-likelihood in this way is processed in the post-coder104 in FIG. 14 into the detected data, and finally, by 9/8 conversion inthe decoder 86 of FIG. 9, into the decoded data.

FIG. 29A to FIG. 29I are time charts which show details of recording andregenerating in the third embodiment. From the data to the head outputof FIG. 29A to FIG. 29E are basically same as the first embodiment ofFIG. 15A to FIG. 15E. The equalizer of FIG. 29E consists of, forexample, 10 tap transversal FIR filters, and the sample point voltagetakes nine (9) values “+5, +3, +2, +1, 0, −1, −2, −3, −5” because of theconvolution code of “3, −2, −3, 2” overlapping each other, therefore,the partial response equalizing waveform which is Nyquist equalizedshown in FIG. 29F is output. The maximum-likelihood detecting circuit ofthe third embodiment performs maximum-likelihood detection like FIG. 29with Viterbi algorithm according to the trellis diagram in FIG. 28, andoutput the output code with maximum-likelihood shown by the solid lineof FIG. 29H. On the other hand, the dotted line is the pathsdisappeared. Finally, 9/8 conversion is performed in the decoder, andthe data of FIG. 29I is output. In this way, whether it is the firstembodiment, the second embodiment or the third embodiment, byincorporating the convolution of (k−s·D) into the regenerating system inorder to reduce the noises in the low-frequency band, the degree offreedom in the transfer characteristic of the equalizer is increased,and it is possible to make filter characteristic suitable to the noisecharacteristic of the medium and the like, therefore optimization of theregenerating system is achieved, and error rate may be improved.

FIG. 30 is basic structure of a fourth embodiment, and the fourthembodiment is wherein (1−D)·(3−2D)·(1+D)² PRML structure is used,wherein, in addition to third embodiment, the convolution of (1+D) inthe regenerating system is also performed.

In FIG. 30, from the NRZI recording system 44 to the magneticregenerating system 48 are basically same as those of the firstembodiment in FIG. 6. The transfer characteristic Q(f) of the nextequalizer 130 is expressed by equation (2), wherein G(f) which is theconvolution in the regenerating system is different. Specifically, G(f)of the fourth embodiment is given byG(f)=(3−2D)·(1+D)²  (5).Therefore, the equalizing target characteristic of the regeneratingsystem which is given by the product of and the cosine roll-offcharacteristic R(f) of the Nyquist equalizer in the right side of theequation (1) and G(f) of the equation (5) is the characteristic 134 ofFIG. 31. The characteristic 56 shown by the dotted line is the cosineroll-off characteristic R(f) of the Nyquist equalizer. From output ofthe equalizer 136, which achieves the equalizing target characteristicin the regenerating system like this, the impulse response waveform 134shown by the solid line of FIG. 32 is obtained. This impulse responsewaveform 136 is the partial response equalizing waveform, which is +3 attime 0, +4 at time 1T, −1 at time 2T, −2 at time 3T, and 0 at othertimes ±nT (n is integer). In this figure, a waveform 138 shown by thedotted line is the partial response equalizing waveform corresponding toa negative impulse. Further, for convenience of description, thewaveform without noises is shown, but actually it is the waveform withconvoluted noises, and fluctuates around the value.

The maximum-likelihood detecting circuit 132 of the fourth embodimentdetects the convolution code according to Viterbi algorithm from thepartial response equalizing waveform with convoluted noises. In thefourth embodiment, the convolution of (1−D) in the recording system andthe convolution of (3−2D)·(1+D)² in the regenerating system has beendone, therefore, expansion to(1−D)·(3−2D)·(1+D)²=3+D−5D ² −D ³+2D ⁴is possible. Therefore, convolution code “3, 1, −5, −1, 2” correspondingto the input code “1” is detected, and the output code is output. Now,specific structure in the case that the basic structure of the fourthembodiment of FIG. 30 is applied to the read channel 30 of the hard diskdrive of FIG. 2 is described. A block diagram in the case that thefourth embodiment is applied to the read channel is same as the firstembodiment of FIG. 9. More specifically, from the recording system tothe sample circuit 80 of the regenerating system are basically same asthe first embodiment, and the equalizer 82 and the maximum-likelihooddetecting circuit 84 have structure unique to the fourth embodiment. Thetransfer characteristic Q(f) of the equalizer circuit 82 in the fourthembodiment, including the transfer characteristic of the low-pass filter78 in the preceding stage, is shown by characteristic 140 of FIG. 33,schematically. In this figure, characteristic 128 shown by the dottedline is the characteristic 128 of the third embodiment in FIG. 26.Comparing to the equalizer transfer characteristic 128 of the thirdembodiment, it is understood that, in the characteristic 140 of thefourth embodiment, by adding the further convolution of (1−D) to theregenerating system, the gain in the high-frequency band is decreased,and the gain in the low-frequency band is increased simultaneously.

FIG. 34 shows the relationship of the equation (1) which givesequalizing target characteristic of the regenerating system in thefourth embodiment, by transfer characteristic diagrams. From FIG. 34, Itis obvious that, along with (3−2D)·(1+D) of the third embodiment, theconvolution of (1+D) is also added to G(f) which gives the convolutionin regenerating system, therefore, the gain in the high-frequency bandis decreased, and the gain in the low-frequency band is increased. Theproduct of G(f) in the regenerating system and the cosine roll-offcharacteristic R(f) of the Nyquist equalizer is the equalizing targetcharacteristic 140 in the regenerating system shown in FIG. 33. In thiscondition, if the transfer characteristic H(f) in the magneticregenerating system is known, the equalizing transfer characteristicQ(f) may be obtained from the equation (2), since the equalizing targetcharacteristic 140 in regenerating system is equivalent to the productof the transfer characteristic H(f) in the magnetic regenerating systemand the equalizing transfer characteristic Q(f). In this point, the VFOcircuit 88 of the fourth embodiment in FIG. 9 may be achieved by priorart, by splitting the equalizer 82 into parts of a (1+D) filter and a(1−D) filter, and inputting the output of the (1+D) filter into the VFOcircuit 88.

Now, the maximum-likelihood detecting circuit 84 of the fourthembodiment is same as that of the first embodiment in principle, butsince one (1) bit is convoluted into five (5) bits, the constraintlength=5, and needed circuit amount is nearly twice as much as that ofthe first embodiment to the third embodiment, wherein the constraintlength=4. Specifically, a square error detecting circuit 94 in themaximum-likelihood detecting circuit of FIG. 14 retains 16 nodecumulative square errors corresponding to 16 nodes in the trellisdiagram of FIG. 35. The cumulative square error calculating circuit 96calculates new 32 branch cumulative square errors by adding 16 nodecumulative square errors and 32 node cumulative square errors,respectively. The compare and select circuit 98 compares the branchcumulative square errors indicated by two arrows in the nodes of theright part of the trellis diagram of FIG. 35, considers that smallerdata has higher likelihood, and outputs the data and select signals to apath memory 102.

Simultaneously, The compare and select circuit 98 outputs the branchcumulative square error corresponding to the selected data to thecumulative square error retaining circuit 100 as new node cumulativesquare error for that node. The path memory 102 consists of multi-stageregisters recording the selected path, records the selected data fromthe compare and select circuit 98, and copies the data in each stageaccording to the select signal, as shown in the trellis diagram of FIG.35. In this way, one half of paths continues to exist in each stage, andthe other half disappears. By repeating this, only the path withmaximum-likelihood will continues to exist on the path memory 102, andthe maximum-likelihood detection will be done. In this way, themaximum-likelihood detecting circuit of the fourth embodiment operatesso that the convolution code “3, 1, −5, −1, 2” is detected in timesequence. The detected data considered as one with maximum-likelihood isprocessed in a post-coder 104 into the detected data, and finally,converted by 9/8 conversion in the decoder 86 of the fourth embodimentof FIG. 9 to the decoded data.

FIG. 36A to FIG. 36I are time charts which show details of recording andregenerating in the fourth embodiment. The data of FIG. 36A to the headoutput of FIG. 36E are same as FIG. 15A to FIG. 15E in the firstembodiment. The output waveform of the equalizer of FIG. 36F consistsof, for example, 10 tap transversal FIRE filters, and the sample pointvoltage in this case is 11 values “+5, +4, +3, +2, +1, 0, −1, −2, −3,−4, −5” because of overlapping of the convolution code of “2, −1, −2, 1”offsetting each other, therefore, the partial response equalizingwaveform which is Nyquist equalized is output as shown. Themaximum-likelihood detecting circuit of FIG. 36G performsmaximum-likelihood detection with Viterbi algorithm according to thetrellis diagram shown in FIG. 35, and the paths shown by the solid lineswill be continued to exist, then the output code of FIG. 36H is output.Finally, by performing 9/8 conversion of the output code, the data ofFIG. 36I is decoded.

In the embodiments, for (k−s·D)·(1+D)^(n) which is the general type ofthe convolution in the regenerating system, in the cases of

k=1, s=1, n=1, which is the first embodiment,

k=1, s=2, n=1, which is the second embodiment,

k=3, s=2, n=1, which is the third embodiment and

k=3, s=2, n=2, which is the fourth embodiment,

are used as examples, but the present invention is not limited to these,and it is possible to set any filter characteristics suitable to mediumnoises and the like by optimizing K, S and n to the transfercharacteristic II(f) in the magnetic regenerating system determined bythe frequency characteristics of the medium and the head.

Also, in the embodiments, though the case of being provided with NRZIcircuit which performs the convolution of (1−D) in the recording systemis used as example, other recording system which does not include theconvolution of (1−D) may be also applicable.

Further, in the embodiments, if a direct current element results inproblems, it may be possible to provide a scrambling circuit before theencoder to randomize the data, and when regenerating, to provide adescrambling circuit after the decoder to restore the data.

Further, in the embodiments, though VFO circuit receives input fromfilter output, the structure which receives input from equalizer outputmay be used.

Further, in the embodiments, though the cases that themaximum-likelihood circuit takes square error is described, thestructure multiplying the constant number including 1 may be used.

Further, the regenerating system after the sample circuit may consist ofanalog circuits, or digital circuit with quantization.

Further, though the write head and the read head are described asseparate heads, these may be identical head. Further, though 8/9 RLLcode is used as example of RLL code, other codes such as 16/17 RLL codemay be applicable.

Further, the present invention includes any appropriate variants insofaras they do not impair objects and advantages of the invention. Thepresent invention is not limited by the numerical values denoted in theembodiments.

INDUSTRIAL APPLICABILITY

As set forth hereinabove, according to the present invention, byincluding at least the convolution of (k−s·D) in the regeneratingsystem, noises with peaks of power in low-frequency band, such as mediumnoises, may be reduced effectively, and with this reduction of noises inlow-frequency band, it may be possible to increase recording density,improve regenerating error rate, and also improve regenerating errorrate with reduction of sidestrokes.

Further, by optimizing integer k and s in the convolution of (k−s·D),the degree of freedom in the transfer characteristic of the equalizer isincreased, and it is possible to easily achieve filter characteristicsuitable to the noise characteristic of the medium and the like, and bythis optimization of integer k and s, it is possible to effectivelyreduce noises in low-frequency band, and increase recording density.Especially, though, since an area of one (1) bit will be closing in onthat of particles of magnetic materials in the future, the medium noiseswould be increased, the noises in low-frequency band can be effectivelyreduced, and significant contribution to the improvement of recordingdensity can be achieved, by including the convolution of (k−s·D) in theregenerating system of the present invention.

1. A signal processing method utilizing a partial response to recordinformation on a medium and then regenerate the information from themedium, wherein a record signal recorded on the medium is subjected tothe convolution of (1−D) in an NRZI recording process, where D: one (1)bit delay operator, wherein a regeneration signal from the medium issubjected to an equalizing process including the convolution of(k−s·D)(1+D)^(n) where D: one (1) bit delay operator, k, s: integer, n:positive integer, and k=1, s=1, n=1, and wherein the information isdecoded from the equalized signal by use of maximum-likelihooddetection, and the maximum-likelihood detection convolution code of(1−D)k−s·D)(1+D)^(n) where D: one (1) bit delay operator, k, s: integer,n: positive integer, and k=1, s=1, n=1.
 2. A signal processing circuitutilizing a partial response to record information on a medium through arecording system and regenerate the information from the medium througha regenerating system, wherein the recording system includes a circuitunit subjecting a record signal recorded on the medium to theconvolution of (1−D) in an NRZI recording circuit, where D: one (1) bitdelay operator, wherein the regeneration system includes an equalizersubjecting an output signal from the medium to the convolution of(k−s·D)(1+D)^(n) where D: one (1) bit delay operator, k, s: integer, n:positive integer, and k=1, s=1,n=1 and wherein the detecting circuitcomprises a maximum-likelihood detector which decodes the informationfrom an output signal of the equalizer by use of maximum-likelihooddetection, and the maximum-likelihood detection convolution code of(1−D)(k−s·D)(1+D)^(n) where D: one (1) bit delay operator, k, s:integer, n: positive integer, and k=1, s=1, n=1.
 3. A signalrecording/regenerating apparatus utilizing a partial response to recordinformation on a medium through a recording system and regenerate theinformation from the medium through a regenerating system, wherein therecord system includes a circuit unit subjecting a record signalrecorded on the medium to convolution of (1−D) in an NRZI recordingcircuit, where D: one (1) bit delay operator, wherein the regenerationsystem includes an equalizer subjecting a regeneration signal from themedium to the convolution of(k−s·D)(1+D)^(n) where D: one (1) bit delay operator, k, s: integer, n:positive integer, and k=1, s=1, n=1 and wherein the detecting circuitcomprises a maximum-likelihood detector which decodes the informationfrom an output signal of the equalizer by use of maximum-likelihooddetection, and the maximum-likelihood detection convolution code of(1−D)(k−s·D)(1+D)^(n) where D: one (1) bit delay operator, k, s:integer, n: positive integer, and k=1, s=1, n=1.